Selecting the best statistical distribution with PROMETHEE and GAIA

Three methods have previously been presented in Computer and Industrial Engineering for the selection of a statistical distribution to describe a data-set: the weighted sum model, the weighted multiplication model and data envelopment analysis. These are based on distinctive preset of parameters and result in three different rankings. In these approaches there is no interaction with the decision-maker (DM). This leads to the question: which method should a DM choose? In this paper, we adopt another approach where the DM is the central actor. Based on the multi-criteria decision aid methods, PROMETHEE and GAIA, we will show that different preference parameters (given by the DM) lead to different rankings. Finally, a group decision can be reached using its extension: PROMETHEE GDSS.

► We study the problem of choosing a statistical distribution matching a data-set.
► Several conflicting criteria can be used to determine the best distribution.
► We use the PROMETHEE and GAIA methods for this choice problem.
► We confirm previous results while introducing decision maker’s preferences.